Description
We are seeking an Engineering Manager / Delivery Lead to own end-to-end delivery execution for Agentic AI solutions within AI & Technology Solutions (ATS), Clinical AI & Technology Innovation (CAITI).
This role is accountable for translating product intent and architectural direction into reliable, compliant, high-quality delivery outcomes, by leading internal teams and external vendors.
Key Responsibilities
- Own end-to-end delivery execution for Agentic AI solutions from Proof of Concept through Production, ensuring predictable, high-quality outcomes.
- Translate product scope and architectural direction into clear delivery plans, sprint cadence, and execution milestones.
- Drive day-to-day engineering delivery, including dependency management, issue resolution, and removal of execution blockers.
- Ensure delivery readiness across environments, CI/CD, quality gates, validation, and release governance.
- Coordinate and orchestrate internal teams and vendors to deliver as a single, integrated delivery unit.
- Partner closely with Product, Architecture, QA, Validation, and Program Management to ensure delivery aligns with regulatory, quality, and governance expectations.
- Provide transparent delivery reporting, proactively surface risks, and escalate issues with clear options and trade-offs.
- Support release and rollout execution (pilot to scale) and ensure effective handover to operations.
- Lead and mentor a multidisciplinary engineering team (AI engineers, data engineers, platform engineers), providing technical guidance, career development, and performance management.
- Act as delivery owner for vendor-contributed work, including task integration, quality expectations, and delivery timelines.
- Ensure vendor outputs meet IQVIA standards and are integrated seamlessly into CI/CD and release processes.
- Surface delivery risks related to vendor dependency early and clearly.
Key Qualifications
- 7+ years in engineering delivery roles, with demonstrated ownership of end-to-end delivery in complex systems.
- Proven experience delivering Agentic AI, AI-enabled, or data-intensive platforms, including systems that incorporate reasoning, orchestration, retrieval, or automation components.
- Experience delivering AI solutions in regulated or highly governed enterprise environments, with accountability for production readiness, auditability, and lifecycle controls.
- Demonstrated ability to coordinate cross-functional teams and external vendors delivering agent-based solutions across prototype, MVP, and production stages.
- Bachelor’s degree with 10+ years of experience, or Master’s degree with 7+ years of experience in Computer Science, Information Systems, or a related technical field.
- Strong understanding of Agentic SDLC / ADLC concepts, including agent lifecycle management, phased progression.
- Experience delivering systems that require agent evaluation, monitoring, and feedback loops, including performance, reliability, and behavioral drift considerations.
- Ability to engage credibly with Solution Architects, Tech Leads, and AI teams on agent feasibility, orchestration complexity, dependency sequencing, and delivery risk.
- Practical understanding of CI/CD for agentic systems, including environment readiness, controlled releases, rollback strategies, and post-deployment monitoring.
- Proficiency in programming languages such as Python, Java, or Scala, with strong understanding of data structures and algorithms.